Bibliographic record
Abstract
Abstract Deep-sea mining is taking another step closer to reality. Early leases for exploration in the central Pacific manganese nodule fields and elsewhere in the oceans are coming to an end, and contractors are faced with a choice—extend the licenses to continue exploration or apply to mine the deposits they have found. The first 15-year licenses were originally signed into effect by the International Seabed Authority (ISA) in 2001 and began to expire in 2016. With no operations in a position to commence mining and, more importantly, no regulations in place to allow it, most exploration licenses were simply renewed. Eight of the original licenses were extended for five more years, some twice, and new licenses have been granted. Today, there are 31 contracts for exploration: 19 for manganese nodules, 7 for sea-floor massive sulfides, and 5 for Co-rich crusts. The first contract for massive sulfide exploration expires in 2026; the first for Co-rich crusts expires in 2029. Meanwhile, there is strong interest from a number of countries in the mineral resource potential of their exclusive economic zones (EEZs), particularly Japan and Norway. Against this backdrop of rapidly shifting exploration activity, it may be time to take another look at marine minerals as a resource for the future. In a report entitled “The Future of the Ocean Economy by 2030,” the Organization for Economic Cooperation and Development (OECD) asked, “What new developments could result in a complete revision of offshore mineral potential?” For most parts of the oceans, the answer to this question is plagued by inadequate mapping and a lack of geologic knowledge as a basis for assessing the resources. However, new approaches to exploration are emerging, and recent discoveries, such as on the continental shelf and beneath the cover of sediment, are changing our view of the resource potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".